In a software program, emotion recognition provides advanced image processing and allows a program to “read” the emotions of a human face. This procedure involves recognition of a person’s emotional state such as anger, sadness, fear, joy, disgust, surprise, trust, and others. Key players focus on combining image processing techniques with sophisticated algorithms to understand more about a person’s feeling with the help of facial images or videos.

Rapid growth in Internet of Things technology, rise in popularity of wearable technology, and high smartphone penetration worldwide drive the global emotion recognition and detection market. However, high cost of application, numerous functional requirements, misinterpretation in analysis of emotions restricts the emotion recognition and detection market growth. Moreover, adoption of cloud-based technology presents a major opportunity for market expansion.

The global emotion detection and recognition market is segmented on the basis of software tool, application, technology, end user, and region. Based on software tool, it is divided into facial expression & emotion recognition, gesture & posture recognition, and voice recognition. Based on application, the emotion recognition and detection industry is classified into law enforcement, surveillance, & monitoring; entertainment & consumer electronics; marketing & advertising; and others. The technology segment includes pattern recognition network, machine learning, natural language processing, and others.